The present invention relates generally to signal processing in a wireless network and more particularly to estimating a signal-to-interference ratio (SIR) in a wireless receiver.
Receivers in wireless networks typically calculate performance parameters to evaluate the receiver and/or to assess certain network level parameters, such as transmit power, data rate, etc. One performance parameter of particular interest to wireless receivers in a spread spectrum network is the signal-to-interference ratio (SIR) associated with the received signals. Conventional receivers typically calculate the SIR associated with the received signals and use the calculated SIR to adapt the network level parameters to current channel conditions. For example, the calculated SIR may be used to control mobile station transmit power, data transmission rate, mobile station scheduling, etc.
The accuracy of network adaptation to current channel conditions depends on the accuracy of the SIR estimates as well as the amount of time expended to generate the SIR estimates. Currently, there are many ways to estimate the SIR in a spread spectrum network. For example, the receiver may use a combination of chip samples and despread symbols to estimate the SIR. While this approach may provide accurate SIR estimates in a timely manner, this approach requires a complex receiver architecture with access to both chip samples and despread values.
Another receiver may use symbol estimates provided by a RAKE receiver output to estimate the SIR. However, because current RAKE output symbols correspond to symbols received well in the past, the resulting SIR does not correspond to current receiver performance and channel conditions. Therefore, while this approach requires a significantly less complex receiver architecture, the resulting SIR estimates are insufficient for real-time operations, such as power control, rate adaptation, etc.
Still other receivers may use despread symbols (pilot or data) to generate a finger SIR for each finger of a RAKE receiver. Summing the finger SIRs provides an SIR estimate that may be used for real-time operations. However, because the despread symbols typically contain a considerable amount of noise, the resulting SIR estimate is often biased. Conventional networks may remove this bias by subtracting an estimate of the bias from the current SIR estimate. However, the bias estimation process can overestimate the bias. As a result, using subtraction to remove the bias can result in negative, and therefore inaccurate, SIR estimates.